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Machine Learning Engineer Intern Jobs in Quebec (NOW HIRING)

Kinaxis Inc.

$100 - $130/hr

In 1984, we started out as a team of three engineers. Today, we have grown to become a global ... What you will do Bring deep expertise in machine learning and applied AI, and you are energized by ...

ABB

... engineer of machine-human interfaces for mine hoist systems. You will be part of ABB Canada ... You'll grow through meaningful work, continuous learning, and support that's tailored to your goals.

Caeus

C-IT-106 - AI Intern

Montreal, QC · Hybrid

Internship dates: From August 31st to December 18th 2026 As an intern within the artificial ... in programming languages such as Python, Java, or C++ * Familiarity with machine learning ...

Ubisoft

Software Engineer - MLOPS

Montreal, QC

As a Machine Learning Operations Software Engineer at Ubisoft Montréal, you will help build reliable and scalable systems that protect the trust and safety of our players . You will join the Player ...

Apertera

Generative AI Engineer

Montreal, QC · On-site

Work closely with machine learning engineers and data engineers to design, build, and test models. * Develop efficient and scalable algorithms for training and inference of generative models ...

ABB

As an electrical engineering intern within our electrification division in Montreal, you will have ... You'll grow through meaningful work, continuous learning, and support that's tailored to your goals.

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All JobsMachine Learning Engineer Intern JobsMachine Learning Engineer Intern Jobs in Quebec

Machine Learning Engineer Intern information

See Quebec salary details

$23K

$120.7K

$215.5K

How much do machine learning engineer intern jobs pay per year?

As of Jul 22, 2026, the average yearly pay for machine learning engineer intern in Quebec is $120,739.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,500.00 and $164,000.00 per year, depending on experience, location, and employer.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive in the Machine Learning Engineer Intern position, and why are they important?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What are the most commonly searched types of Machine Learning Engineer jobs in Quebec? The most popular types of Machine Learning Engineer jobs in Quebec are:
What are popular job titles related to Machine Learning Engineer Intern jobs in Quebec? For Machine Learning Engineer Intern jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Intern jobs in Quebec look for? The top searched job categories for Machine Learning Engineer Intern jobs in Quebec are:
What cities in Quebec are hiring for Machine Learning Engineer Intern jobs? Cities in Quebec with the most Machine Learning Engineer Intern job openings:
Machine Learning Engineer Intern jobs near you
Infographic showing various Machine Learning Engineer Intern job openings in Quebec as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution, with an average salary of $120,739 per year, or $58 per hour.

Machine Learning Research Scientist

Valence Labs

Montreal, QC • Hybrid

Other

Posted 20 days ago

Job description

About Valence Labs

Valence Labs is Recursion's frontier AI research engine. We lead high-impact research
programs designed to materially expand Recursion's ability to discover and develop medicines for complex diseases. Our team balances near-term pragmatism with a long-term view of where the field is heading in the next 3-5 years, incubating, designing, and productizing the approaches we believe will define the future of drug discovery. 

Our work is driven by optimism, purpose, and a shared vision for a healthier tomorrow. We publish in top journals and conferences, contribute to open science, and engage with some of the world's most active ML-for-drug-discovery research communities. Our teams are based in London and Montreal, with deep ties to Mila, the world's largest deep-learning research institute.

About the role

We are seeking a Research Scientist with a hybrid research-engineering mindset to join our team. In this role, you will be at the forefront of developing generative architectures and foundation models that ground machine learning in real-world biological discovery. 

A successful candidate will have most of the following:

  • PhD (or equivalent) with significant academic or industry research experience in a related technical field involving machine learning applied to drug discovery.
  • Scientific knowledge of biology, chemistry, or physics, along with previous experience working in a scientific environment across disciplines.
  • Impactful research track record, including designing new neural networks to model molecular or biological systems, proposing new theories, or applying novel ML techniques to real-world problems.
  • Strong technical and engineering skills, including the ability to rapidly prototype ML models (Python proficiency required; Rust preferred for high performance molecular encoding or data pipelines).
  • Leadership and communication skills, including a lead authorship record in peer-reviewed conferences (e.g., NeurIPS, ICML, ICLR) or journals (e.g., Nature, Science, JACS).
  • Interdisciplinary empathy, with a proven ability to work effectively with interdisciplinary teams of dry and wet scientists.

Key Responsibilities 

  • Model Innovation: Research and develop state-of-the-art architectures (e.g., flow matching, diffusion models, geometric deep learning) tailored to specific biological or chemical challenges.
  • Scalable Engineering: Build and maintain ML systems capable of processing massive datasets on high-performance compute clusters (BioHive).
  • Biological Grounding: Ensure ML predictions are biologically trustworthy and actionable by collaborating closely with drug discovery teams.
  • Open Science & Collaboration: Publish findings in top-tier venues and contribute to the broader scientific community. 

Working Location & Compensation:

This is an office-based, hybrid position at either of our offices located in Montreal, Quebec, Canada. Employees are expected to work in the office at least 50% of the time.

Compensation packages are competitive and commensurate with the skills and level of experience required for this role. In addition to base salary you will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. 

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